{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-19T04:21:03.797032Z",
     "start_time": "2020-10-19T04:21:03.165300Z"
    }
   },
   "outputs": [],
   "source": [
    "import torch\n",
    "import torchvision\n",
    "import torchvision.transforms as transforms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-19T11:07:46.968438Z",
     "start_time": "2020-10-19T11:07:44.636943Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Files already downloaded and verified\n",
      "Files already downloaded and verified\n"
     ]
    }
   ],
   "source": [
    "transform = transforms.Compose(\n",
    "    [transforms.ToTensor(),\n",
    "     transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])\n",
    "\n",
    "trainset = torchvision.datasets.CIFAR10(root='./data', train=True,\n",
    "                                        download=True, transform=transform)\n",
    "trainloader = torch.utils.data.DataLoader(trainset, batch_size=4,\n",
    "                                          shuffle=True, num_workers=2)\n",
    "\n",
    "testset = torchvision.datasets.CIFAR10(root='./data', train=False,\n",
    "                                       download=True, transform=transform)\n",
    "testloader = torch.utils.data.DataLoader(testset, batch_size=4,\n",
    "                                         shuffle=False, num_workers=2)\n",
    "\n",
    "classes = ('plane', 'car', 'bird', 'cat',\n",
    "           'deer', 'dog', 'frog', 'horse', 'ship', 'truck')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-19T14:13:37.340355Z",
     "start_time": "2020-10-19T14:13:36.931236Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  cat   car horse horse\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "%matplotlib inline\n",
    "\n",
    "# functions to show an image\n",
    "\n",
    "\n",
    "def imshow(img):\n",
    "    img = img / 2 + 0.5     # unnormalize\n",
    "    npimg = img.numpy()\n",
    "    plt.imshow(np.transpose(npimg, (1, 2, 0)))\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "# get some random training images\n",
    "dataiter = iter(trainloader)\n",
    "images, labels = dataiter.next()\n",
    "\n",
    "# show images\n",
    "imshow(torchvision.utils.make_grid(images))\n",
    "# print labels\n",
    "print(' '.join('%5s' % classes[labels[j]] for j in range(4)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-19T14:13:57.948819Z",
     "start_time": "2020-10-19T14:13:57.935355Z"
    }
   },
   "outputs": [],
   "source": [
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "\n",
    "\n",
    "class Net(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(Net, self).__init__()\n",
    "        self.conv1 = nn.Conv2d(3, 6, 5)\n",
    "        self.pool = nn.MaxPool2d(2, 2)\n",
    "        self.conv2 = nn.Conv2d(6, 16, 5)\n",
    "        self.fc1 = nn.Linear(16 * 5 * 5, 120)\n",
    "        self.fc2 = nn.Linear(120, 84)\n",
    "        self.fc3 = nn.Linear(84, 10)\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = self.pool(F.relu(self.conv1(x)))\n",
    "        x = self.pool(F.relu(self.conv2(x)))\n",
    "        x = x.view(-1, 16 * 5 * 5)\n",
    "        x = F.relu(self.fc1(x))\n",
    "        x = F.relu(self.fc2(x))\n",
    "        x = self.fc3(x)\n",
    "        return x\n",
    "\n",
    "\n",
    "net = Net()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-19T14:14:16.072965Z",
     "start_time": "2020-10-19T14:14:16.068104Z"
    }
   },
   "outputs": [],
   "source": [
    "import torch.optim as optim\n",
    "\n",
    "criterion = nn.CrossEntropyLoss()\n",
    "optimizer = optim.SGD(net.parameters(), lr=0.001, momentum=0.9)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FUCK ME"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-19T14:18:04.470211Z",
     "start_time": "2020-10-19T14:14:56.203059Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1,  2000] loss: 2.235\n",
      "[1,  4000] loss: 1.855\n",
      "[1,  6000] loss: 1.674\n",
      "[1,  8000] loss: 1.573\n",
      "[1, 10000] loss: 1.509\n",
      "[1, 12000] loss: 1.462\n",
      "[2,  2000] loss: 1.394\n",
      "[2,  4000] loss: 1.350\n",
      "[2,  6000] loss: 1.333\n",
      "[2,  8000] loss: 1.320\n",
      "[2, 10000] loss: 1.294\n",
      "[2, 12000] loss: 1.271\n",
      "Finished Training\n"
     ]
    }
   ],
   "source": [
    "for epoch in range(2):  # loop over the dataset multiple times\n",
    "\n",
    "    running_loss = 0.0\n",
    "    for i, data in enumerate(trainloader, 0):\n",
    "        # get the inputs; data is a list of [inputs, labels]\n",
    "        inputs, labels = data\n",
    "\n",
    "        # zero the parameter gradients\n",
    "        optimizer.zero_grad()\n",
    "\n",
    "        # forward + backward + optimize\n",
    "        outputs = net(inputs)\n",
    "        loss = criterion(outputs, labels)\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "\n",
    "        # print statistics\n",
    "        running_loss += loss.item()\n",
    "        if i % 2000 == 1999:    # print every 2000 mini-batches\n",
    "            print('[%d, %5d] loss: %.3f' %\n",
    "                  (epoch + 1, i + 1, running_loss / 2000))\n",
    "            running_loss = 0.0\n",
    "\n",
    "print('Finished Training')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-19T14:18:51.416936Z",
     "start_time": "2020-10-19T14:18:26.380355Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "GroundTruth:    cat  ship  ship plane\n",
      "Predicted:   bird  ship  ship  ship\n",
      "Accuracy of the network on the 10000 test images: 52 %\n",
      "Accuracy of plane : 62 %\n",
      "Accuracy of   car : 70 %\n",
      "Accuracy of  bird : 59 %\n",
      "Accuracy of   cat : 38 %\n",
      "Accuracy of  deer : 20 %\n",
      "Accuracy of   dog : 21 %\n",
      "Accuracy of  frog : 79 %\n",
      "Accuracy of horse : 54 %\n",
      "Accuracy of  ship : 78 %\n",
      "Accuracy of truck : 37 %\n"
     ]
    }
   ],
   "source": [
    "PATH = './cifar_net.pth'\n",
    "torch.save(net.state_dict(), PATH)\n",
    "dataiter = iter(testloader)\n",
    "images, labels = dataiter.next()\n",
    "\n",
    "# print images\n",
    "imshow(torchvision.utils.make_grid(images))\n",
    "print('GroundTruth: ', ' '.join('%5s' % classes[labels[j]] for j in range(4)))\n",
    "\n",
    "net = Net()\n",
    "net.load_state_dict(torch.load(PATH))\n",
    "\n",
    "outputs = net(images)\n",
    "\n",
    "_, predicted = torch.max(outputs, 1)\n",
    "\n",
    "print('Predicted: ', ' '.join('%5s' % classes[predicted[j]]\n",
    "                              for j in range(4)))\n",
    "\n",
    "correct = 0\n",
    "total = 0\n",
    "with torch.no_grad():\n",
    "    for data in testloader:\n",
    "        images, labels = data\n",
    "        outputs = net(images)\n",
    "        _, predicted = torch.max(outputs.data, 1)\n",
    "        total += labels.size(0)\n",
    "        correct += (predicted == labels).sum().item()\n",
    "\n",
    "print('Accuracy of the network on the 10000 test images: %d %%' % (\n",
    "    100 * correct / total))\n",
    "\n",
    "class_correct = list(0. for i in range(10))\n",
    "class_total = list(0. for i in range(10))\n",
    "with torch.no_grad():\n",
    "    for data in testloader:\n",
    "        images, labels = data\n",
    "        outputs = net(images)\n",
    "        _, predicted = torch.max(outputs, 1)\n",
    "        c = (predicted == labels).squeeze()\n",
    "        for i in range(4):\n",
    "            label = labels[i]\n",
    "            class_correct[label] += c[i].item()\n",
    "            class_total[label] += 1\n",
    "\n",
    "\n",
    "for i in range(10):\n",
    "    print('Accuracy of %5s : %2d %%' % (\n",
    "        classes[i], 100 * class_correct[i] / class_total[i]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
